Documentos donde el Autor es "Dzul Lopez, Luis"

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Número de documentos: 7.

2023

Artículo Materias > Biomedicina
Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Inglés A novel approach is presented in this study for the classification of lower limb disorders, with a specific emphasis on the knee, hip, and ankle. The research employs gait analysis and the extraction of PoseNet features from video data in order to effectively identify and categorize these disorders. The PoseNet algorithm facilitates the extraction of key body joint movements and positions from videos in a non-invasive and user-friendly manner, thereby offering a comprehensive representation of lower limb movements. The features that are extracted are subsequently standardized and employed as inputs for a range of machine learning algorithms, such as Random Forest, Extra Tree Classifier, Multilayer Perceptron, Artificial Neural Networks, and Convolutional Neural Networks. The models undergo training and testing processes using a dataset consisting of 174 real patients and normal individuals collected at the Tehsil Headquarter Hospital Sadiq Abad. The evaluation of their performance is conducted through the utilization of K-fold cross-validation. The findings exhibit a notable level of accuracy and precision in the classification of various lower limb disorders. Notably, the Artificial Neural Networks model achieves the highest accuracy rate of 98.84%. The proposed methodology exhibits potential in enhancing the diagnosis and treatment planning of lower limb disorders. It presents a non-invasive and efficient method of analyzing gait patterns and identifying particular conditions. metadata Siddiqui, Hafeez Ur Rehman; Saleem, Adil Ali; Raza, Muhammad Amjad; Gracia Villar, Santos; Dzul Lopez, Luis; Diez, Isabel de la Torre; Rustam, Furqan y Dudley, Sandra mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, santos.gracia@uneatlantico.es, luis.dzul@unini.edu.mx, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR (2023) Empowering Lower Limb Disorder Identification through PoseNet and Artificial Intelligence. Diagnostics, 13 (18). p. 2881. ISSN 2075-4418

Artículo Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Inglés Agriculture is a critical domain, where technology can have a significant impact on increasing yields, improving crop quality, and reducing environmental impact. The use of renewable energy sources such as solar power in agriculture has gained momentum in recent years due to the potential to reduce the carbon footprint of farming operations. In addition to providing a source of clean energy, solar tracking systems can also be used for remote weather monitoring in the agricultural field. The ability to collect real-time data on weather parameters such as temperature, humidity, and rainfall can help farmers make informed decisions on irrigation, pest control, and other crop management practices. The main idea of this study is to present a system that can improve the efficiency of solar panels to provide constant power to the sensor in the agricultural field and transfer real-time data to the app. This research presents a mechanism to improve the arrangement of a photovoltaic (PV) array with solar power and to produce maximum energy. The proposed system changes its direction in two axes (azimuth and elevation) by detecting the difference between the position of the sun and the panel to track the sun using a light-dependent resistor. A testbed with a hardware experimental setup is designed to test the system’s capability to track according to the position of the sun effectively. In the end, real-time data are displayed using the Android app, and the weather data are transferred to the app using a GSM/WiFi module. This research improves the existing system, and results showed that the relative increase in power generation was up to 52%. Using intelligent artificial intelligence techniques with the QoS algorithm, the quality of service produced by the existing system is improved. metadata Kanwal, Tabassum; Rehman, Saif Ur; Ali, Tariq; Mahmood, Khalid; Gracia Villar, Santos; Dzul Lopez, Luis y Ashraf, Imran mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, santos.gracia@uneatlantico.es, luis.dzul@unini.edu.mx, SIN ESPECIFICAR (2023) An Intelligent Dual-Axis Solar Tracking System for Remote Weather Monitoring in the Agricultural Field. Agriculture, 13 (8). p. 1600. ISSN 2077-0472

Artículo Materias > Ingeniería Universidad Europea del Atlántico > Investigación > Producción Científica
Fundación Universitaria Internacional de Colombia > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros
Universidad Internacional Iberoamericana Puerto Rico > Investigación > Producción Científica
Universidad Internacional do Cuanza > Investigación > Producción Científica Abierto Inglés Railway track faults may lead to railway accidents and cause human and financial loss. Spatial, temporal, and weather elements, and wear and tear, lead to ballast, loose nuts, misalignment, and cracks leading to accidents. Manual inspection of such defects is time-consuming and prone to errors. Automatic inspection provides a fast, reliable, and unbiased solution. However, highly accurate fault detection is challenging due to the lack of public datasets, noisy data, inefficient models, etc. To obtain better performance, this study presents a novel approach that relies on mel frequency cepstral coefficient features from acoustic data. The primary objective of this study is to increase fault detection performance. As well as designing an ensemble model, we utilize selective features using chi-square(chi2) that have high importance with respect to the target class. Extensive experiments were carried out to analyze the efficiency of the proposed approach. The experimental results suggest that using 60 features, 40 original features, and 20 chi2 features produces optimal results both regarding accuracy and computational complexity. A mean accuracy score of 0.99 was obtained using the proposed approach with machine learning models using the collected data. Moreover, this performance was significantly better than that of existing approaches; however, the performance of models may vary in real-world settings. metadata Rustam, Furqan; Ishaq, Abid; Hashmi, Muhammad Shadab Alam; Siddiqui, Hafeez Ur Rehman; Dzul Lopez, Luis; Castanedo Galán, Juan y Ashraf, Imran mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, luis.dzul@unini.edu.mx, juan.castanedo@uneatlantico.es, SIN ESPECIFICAR (2023) Railway Track Fault Detection Using Selective MFCC Features from Acoustic Data. Sensors, 23 (16). p. 7018. ISSN 1424-8220

2021

Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Cerrado Inglés Kinetic rigidity of several polymers such as 2,6-bis(3-aminophenoxy)benzonitrile/4,4′oxydiphthalic anhydride (β-CN)APB/ODPA, poly[(2,2-dimethyl-1,3-dioxolan-4-yl)methyl acrylate)] (PACGA), and diglycidyl ether of bisphenol A (DEGEBA) was studied. Rigidity parameter D, Vogel’s temperature T0, and the activation energy Uα (Tg) for the glass transition were evaluated through Vogel’s model along with relaxation data using “nonlinear” regression of Arrhenius function. The existence of certain functional groups within the structure, such as the aromatic rings, gives high level of kinetic rigidity to the structure as is the case of (β-CN)APB/ODPA and DEGEBA, while the aliphatic groups confer flexibility, as in PACGA. metadata Pali-Casanova, Ramón; González, Wadi Elim Sosa; Zavala Loría, José del Carmen; García, Asteria Narváez; Yam Cervantes, Marcial Alfredo; Vega, Manuel de Jesús Aguilar y Dzul Lopez, Luis mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, luis.dzul@unini.edu.mx (2021) Structure and kinetic rigidity of polymers as related to chain relaxations. Journal of Thermoplastic Composite Materials, 34 (5). pp. 596-613. ISSN 0892-7057

2019

Artículo Materias > Ingeniería Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Cerrado Inglés Six aromatic copolyamides contanining phenyl groups were synthesized and characterized. The concentrations of the para-linked phenyl groups and meta-linked phenyl groups were varied systematically on the copolymers general structure to obtain a set of random copolyamides. Effect of copolymerization on glass transition temperature (Tg), tensile modulus (E), Tensile strength (σ) were measured. Changes in density were determined to estimate the effect on Fractional Free Volume (FFV). Results indicate that the substitution of para-linked phenyl group by meta-linked phenyl group causes an increase in tensile modulus E and tensile strength a decrease in Tg. The observed results are attributed to the asymmetric position of the linkages in the TERE and ISO isomers, because symmetric linkages, such as TERE, induces a higher packing of the polyamide chains while the asymmetry of ISO isomer inhibits packing causing an expansion in the FFV. metadata Pali-Casanova, Ramón; Loría-Bastarrachea, María; Aguilar-Vega, M. J.; Zavala-Loría, José; Dzul Lopez, Luis y Yam Cervantes, Marcial Alfredo mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, luis.dzul@unini.edu.mx, SIN ESPECIFICAR (2019) Structure effect on mechanical and thermal properties in aromatic copolyamides with phenyl substituents. Journal of Polymer Research, 26 (10). ISSN 1022-9760

2018

Artículo Materias > Biomedicina Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Cerrado Inglés During the process of beeswax recycling, many industrial derivatives are obtained. These matrices may have an interesting healthy and commercial potential but to date they have not been properly studied. The aim of the present work was to evaluate the proximal and phytochemical composition, the antioxidant capacity and cytotoxic effects of two by-products from beeswax recycling process named MUD 1 and MUD 2 on liver hepatocellular carcinoma. Our results showed that MUD 1 presented the highest (P < .05) fiber, protein, carbohydrate, polyphenol and flavonoid concentration, as well as the highest (P < .05) total antioxidant capacity than the MUD 2 samples. MUD1 exerted also anticancer activity on HepG2 cells, by reducing cellular viability, increasing intracellular ROS levels and affecting mitochondrial functionality in a dose-dependent manner. We showed for the first time that by-products from beeswax recycling process can represent a rich source of phytochemicals with high total antioxidant capacity and anticancer activity; however, further researches are necessary to evaluate their potentiality for human health by in vivo studies. metadata Giampieri, Francesca; Quiles, José L.; Orantes-Bermejo, Francisco J.; Gasparrini, Massimiliano; Forbes-Hernandez, Tamara Y.; Sánchez-González, Cristina; Llopis, Juan; Rivas-García, Lorenzo; Afrin, Sadia; Varela-López, Alfonso; Cianciosi, Danila; Reboredo-Rodriguez, Patricia; Fernández-Piñar, Cristina Torres; Caderón Iglesia, Rubén; Ruiz Salces, Roberto; Aparicio Obregón, Silvia; Crespo-Álvarez, Jorge; Dzul Lopez, Luis; Xiao, Jianbo y Battino, Maurizio mail SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, SIN ESPECIFICAR, ruben.calderon@uneatlantico.es, roberto.ruiz@uneatlantico.es, silvia.aparicio@uneatlantico.es, jorge.crespo@uneatlantico.es, luis.dzul@unini.edu.mx, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es (2018) Are by-products from beeswax recycling process a new promising source of bioactive compounds with biomedical properties? Food and Chemical Toxicology, 112. pp. 126-133. ISSN 0278-6915

2017

Artículo Materias > Biomedicina Universidad Europea del Atlántico > Investigación > Producción Científica
Universidad Internacional Iberoamericana México > Investigación > Artículos y libros Cerrado Inglés Among gynaecological cancers, ovarian cancer represents the leading cause of death in women. Current treatment for ovarian cancer entails surgery followed by combined chemotherapy with platinum and taxane, which are associated, particularly cisplatin, with severe side effects. While this treatment approach appears to be initially effective in a high number of patients, nearly 70% of them suffer a relapse within a few months after initial treatment. Therefore, more effective and better-tolerated treatment options are clearly needed. In recent years, several natural compounds (such as curcumin, epigallocatechin 3-gallate (EGCG), resveratrol, sulforaphane and Withaferin-A), characterized by long-term safety and negligible and/or inexistent side effects, have been proposed as possible adjuvants of traditional chemotherapy. Indeed, several in vitro and in vivo studies have shown that phytocompounds can effectively inhibit tumor cell proliferation, stimulate autophagy, induce apoptosis, and specifically target ovarian cancer stem cells (CSCs), which are generally considered to be responsible for tumor recurrence in several types of cancer. Here we review current literature on the role of natural products in ovarian cancer chemoprevention, highlighting their effects particularly on the regulation of inflammation, autophagy, proliferation and apoptosis, chemotherapy resistance, and ovarian CSC growth. metadata Pistollato, Francesca; Calderón Iglesias, Rubén; Ruiz Salces, Roberto; Aparicio Obregón, Silvia; Crespo Alvare, Jorge; Dzul Lopez, Luis; Giampieri, Francesca y Battino, Maurizio mail SIN ESPECIFICAR, ruben.calderon@uneatlantico.es, roberto.ruiz@uneatlantico.es, silvia.aparicio@uneatlantico.es, jorge.crespo@uneatlantico.es, luis.dzul@unini.edu.mx, SIN ESPECIFICAR, maurizio.battino@uneatlantico.es (2017) The use of natural compounds for the targeting and chemoprevention of ovarian cancer. Cancer Letters, 411. pp. 191-200. ISSN 0304-3835

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<a href="/28573/1/1-s2.0-S0033350626001848-main.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>

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Association between socioeconomic and health variables and community-acquired pneumonia mortality rates in Chile from 1990 to 2021

Objectives To describe long-term trends in mortality attributed to community-acquired pneumonia (CAP) in Chile from 1990 to 2021, stratified by age group, and to evaluate associations with selected socioeconomic and demographic indicators. Study design Ecological, observational, longitudinal study using national secondary data. Methods CAP mortality rates were analyzed for the total population and by age group. Associations with the Human Development Index (HDI), poverty rate, aging index, and life expectancy at birth were examined using a hierarchical analytical approach. This included Spearman's rank correlation for initial exploration, multivariable linear regression to assess adjusted associations, and Prais–Winsten generalized least squares regression to account for first-order autocorrelation and shared temporal trends. Stationarity was evaluated using augmented Dickey–Fuller tests, with supplementary analyses using first-differenced variables. Missing data were imputed using time-based regression or interpolation, with sensitivity analyses performed. Results CAP mortality declined substantially across all age groups over the study period. Strong bivariate correlations were observed between mortality and all socioeconomic indicators; however, these associations were attenuated after adjustment for confounding and temporal autocorrelation. In multivariable and time-series models, HDI and the aging index remained significantly associated with CAP mortality in children (0–9 years) and older adults (≥65 years), whereas associations in intermediate age groups were not robust after accounting for shared secular trends. Poverty and life expectancy did not demonstrate independent associations in adjusted models. Conclusions CAP mortality in Chile has decreased markedly over the past three decades. Associations with socioeconomic indicators are strongest at the extremes of age and persist after accounting for temporal structure, although the ecological design precludes causal inference. These findings highlight the importance of considering demographic and socioeconomic context in population-level analyses of infectious disease outcomes.

Artículos y libros

Italo Salvador López Muñoz mail italo.lopez@doctorado.unini.edu.mx, Maria Loreto Romero Ladrón de Guevara mail , Christian R. Mejia mail , Shyla Del-Aguila-Arcentales mail , Aldo Alvarez-Risco mail , Neal M. Davies mail , Jaime A. Yáñez mail ,

López Muñoz

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An Integrated Machine Learning and Genomic Framework for Precise Detection of Gastric Cancer

This study presents a novel integrative approach for the analysis of high-dimensional gene expression data, leveraging the complementary strengths of unsupervised clustering and supervised classification. Using K-means clustering, the dataset is stratified into three distinct clusters, revealing intrinsic biological patterns and relationships. The resulting cluster assignments are subsequently employed as pseudo-labels to train machine learning models, including support vector machines, random forest, and a stacking ensemble classifier. To validate and enhance the robustness of clustering, complementary methodologies such as hierarchical clustering and DBSCAN are employed, with results visualized through PCA-driven dimensionality reduction. The high predictive accuracy achieved by the classifiers underscores the separability and reliability of the identified clusters. Furthermore, feature importance analysis highlighted key genetic determinants within each cluster, offering actionable insights into potential biomarkers and critical genomic features. This framework bridges the gap between exploratory unsupervised learning and predictive supervised modeling, providing a scalable and interpretable methodology for analyzing complex genomic datasets. Its applicability extends to biomarker discovery, patient stratification, and other precision medicine applications, emphasizing its utility in advancing genomic research and clinical practice.

Producción Científica

Eshmal Iman mail , Sohail Jabbar mail , Shabana Ramzan mail , Ali Raza mail , Farwa Raoof mail , Stefanía Carvajal-Altamiranda mail stefania.carvajal@uneatlantico.es, Vivian Lipari mail vivian.lipari@uneatlantico.es, Imran Ashraf mail ,

Iman

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A novel approach for disease and pests detection in potato production system based on deep learning

Vulnerability of potato crops to diseases and pest infestation can affect its quality and lead to significant yield losses. Timely detection of such diseases can help take effective decisions. For this purpose, a deep learning-based object detection framework is designed in this study to identify and classify major potato diseases and pests under real-world field conditions. A total of 2,688 field images were collected from two research farms in Punjab, Pakistan, across multiple growth stages in various seasonal conditions. Excluding 285 symptoms-free images from the earliest collection led to 2,403 images which were annotated into four biotic-stress classes: blight disease (n = 630), leaf spot disease (n = 370), leafroll virus (viral symptom complex; n = 888), and Colorado potato beetle (larvae/adults; n = 515), indicating class imbalance. Several state-of-the-art models were used including YOLOv8 variants (n/s/m), YOLOv7, YOLOv5, and Faster R-CNN, and the results are discussed in relation to recent potato disease classification studies involving cropped leaf images. Stratified splitting (70% training, 20% validation, 10% testing) was applied to preserve class distribution across all subsets. YOLOv8-medium achieve the best performance with mean average precision (mAP)@0.5 of 98% on the held-out test images. Results for stable 5-fold cross-validation show a mean mAP@0.5 of 97.8%, which offers a balance between accuracy and inference time. Model robustness was evaluated using 5-fold cross-validation and repeated training with different random seeds, showing a low variance of ±0.4% mAP. Results demonstrate promising outcomes under the real-world field conditions, while, broader cross-region and cross-season validation is intended for the future.

Producción Científica

Ahmed Abbas mail , Saif Ur Rehman mail , Khalid Mahmood mail , Santos Gracia Villar mail santos.gracia@uneatlantico.es, Luis Alonso Dzul López mail luis.dzul@uneatlantico.es, Aseel Smerat mail , Imran Ashraf mail ,

Abbas

<a href="/28320/1/1-s2.0-S1876034126000912-main.pdf" class="ep_document_link"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>

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Concern for mpox infection in Latin America

Background Mpox arrived in Latin America and quickly began to replicate, so it is important to measure the concern it generates among residents. The study aims to assess whether country or other factors are associated with concern about mpox infection in Latin America. Methods The study uses a cross-sectional, multicenter design. Sampling was conducted using non-random snowball sampling. From August to September 2022, concern about being infected with mpox was assessed using a previously validated questionnaire (Cronbach's Alpha: 0.85); it was divided into nine countries and other social variables. Results From 1404 respondents, the majority of respondents were female (60.3%) and young (median age 25 years); also, a few reported that it was a significant problem (6% almost all the time and 11% often) and were concerned (6% almost all the time and 11% often) about the possibility of mpox infection. In multivariate analysis, men (aPR: 0.85; 95% CI: 0.73–0.99; p-value=0.046), younger (aPR: 0.98; 95% CI: 0.97–0.99; p-value<0.001), single (aPR: 0.78; 95% CI: 0.62–0.99; p-value=0.042) and, compared to Peru, those living in Colombia (aPR: 0.75; 95% CI. 0.58–0.97; p-value=0.027) and Costa Rica (aPR: 0.65; 95% CI: 0.44–0.96; p-value=0.032) reported the lowest concern; also, Bolivia (aPR: 1.16; 95% CI: 0.94–1.43; p-value=0.176) and Honduras (aPR: 1.01; 95% CI: 0.80–1.27; p-value=0.943) reported that their concerns tend to be higher. Conclusions There were evident differences across respondents' countries; these baseline results show that the first report was made in many countries that were also significantly affected by mpox and now face a new epidemic threatening public health.

Artículos y libros

Christian R. Mejia mail , Aldo Alvarez-Risco mail , Luciana Daniela Garlisi-Torales mail , Telmo Raúl Aveiro mail , Jamil Cedillo-Balcázar mail , Néstor Valentin Rocha-Saravia mail , Andrea Retana-González mail , Medally C. Paucar mail , Beatriz Mejia Raudales mail , Jose Armada mail , Shyla Del-Aguila-Arcentales mail , Neal M. Davies mail , Jaime A. Yáñez mail jaime.yanez@unini.edu.mx,

Mejia

<a class="ep_document_link" href="/28323/1/s40520-026-03363-x_reference.pdf"><img class="ep_doc_icon" alt="[img]" src="/style/images/fileicons/text.png" border="0"/></a>

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Fish consumption and brain structure: a comprehensive systematic review of observational studies

Background Age-related structural changes in the human brain, including cortical atrophy, reductions in grey and white matter volumes, and the accumulation of small vessel–related lesions such as white matter hyperintensities (WMH) and cerebral microbleeds, represent critical biological substrates underlying cognitive decline and dementia. Fish consumption has been associated with slower cognitive decline and reduced risk of dementia, but a comprehensive evaluation of its relation with brain structures is lacking. Aims The aim of this study was to systematically review current scientific literature providing evidence of relation between fish intake and brain structures in human studies. Methods Studies indexed in two major electronic databases have been screened based on a combination of keywords and MeSH terms. Studies were eligible whether they assessed fish consumption in relation to brain structures in the adult populations. Results A total of 24 studies conducted predominantly on older adults met inclusion criteria. Most brain volume measures were obtained via magnetic resonance imaging (MRI) procedures. Higher fish consumption was associated with reduced severity of white matter hyperintensities (a biomarker of cerebral small vessel disease and white matter damage) and cerebral micro-bleed, preservation of certain brain areas volumes (i.e., hippocampus, temporal lobe and periventricle white matter) and cortical thickness of specific areas (i.e., precuneus, parietal, and cingulate grey matter), among others, compared to lower intake. Some analyses found no association and isolated findings suggested possible adverse associations that were not consistently replicated. Studies reporting null findings may underline the possible relevance of the overall diet (i.e., adherence to the Mediterranean diet). Conclusions Inclusion of fish in a healthy and balanced diet is associated with better white matter grades on MRI and slower progression of white matter hyperintensities and reduction of vascular-related lesions of the aging brain, suggesting a potential role in preventing neurocognitive deterioration. Heterogeneity across studies underscores the need for additional studies.

Producción Científica

Justyna Godos mail , Giuseppe Caruso mail , Agnieszka Micek mail , Alberto Dolci mail , Zoltan Ungvari mail , Andrea Lehoczki mail , Lisandra León Brizuela mail , Evelyn Frias-Toral mail , Andrea Di Mauro mail , Mario Siervo mail , Michelino Di Rosa mail , Giuseppe Grosso mail ,

Godos